Method for calibrating vehicle headlights

Abstract

The invention relates to a method (1) for calibrating vehicle headlights. An incorrect position of a pre-defined light distribution is determined by evaluating images of at least one vehicle camera. The invention is characterized in that in a first step (2), at least three images are captured, wherein a first image (3) is captured with a calibration pattern (4), a second image (5) is capture without the calibration pattern (4), and a third image (6) is captured with the inverse calibration pattern (4'); and in a second step (7), the second captured image (5) is subtracted from the first and third captured image (3, 6) in order to clean up the captured images (3, 6) of an existing scene.

Description

[0001] Procedure for calibrating vehicle headlights

[0002] The invention relates to a method for calibrating vehicle headlights according to the type defined in the preamble of claim 1.

[0003] In principle, methods for calibrating vehicle headlights are known from the state of the art. Such methods are necessary because vehicle headlights are often misaligned. Even in vehicles with automatic headlight leveling, mechanical stresses, thermal expansion and contraction, and step losses of built-in stepper motors can occur over time. All of these factors lead to a gradual misalignment of the headlights.

[0004] Vertical misalignments, in particular, pose a safety-related problem, as they can dazzle oncoming traffic or reduce your own visibility. Therefore, headlight adjustments should be checked regularly.

[0005] For example, DE 10 2020 007 613 A1 discloses a method for generating a three-dimensional depth information map of an environment. Light patterns are projected into the environment using a projector and recorded with a camera. The camera images can then be evaluated, whereby the respective positions of feature points on their corresponding epipolar lines are detected, and depth information relating to the three-dimensional map is obtained by determining a displacement of the feature points on these lines. Further prior art is shown in DE 10 2017 222 708 A1. This describes a camera device for a vehicle that can perform 3D environment detection. This requires at least two camera modules with at least partially overlapping detection areas. A control unit, an evaluation unit, and a point light projector can be used to capture 3D environments using a "pseudo-noise pattern."

[0006] DE 10 2016 118801 A1 describes a method for adjusting the headlights of a vehicle. For this purpose, the individual headlight units are controlled at staggered times to illuminate a scene. The scene is recorded over a specified period of time using a camera mounted on the vehicle. The brightness distribution patterns resulting from the staggered control of the plurality of headlight units allow deviations from a reference pattern to be calculated. The headlights can then be adjusted based on the deviations. For further information on the state of the art, reference can be made to DE10 2012 007 908 A1, DE 10 2016 006 391 A1, DE 10 2011 109 440 A1, DE 10 2015 203 889 A1, DE 10 2014 117 845 A1, DE 10 2017 117 594 A1 and DE 10 2020 000 292 A1.

[0007] Stepper motors are used to actively adjust the headlights, for example for headlight range control or cornering light functions. These can adjust the light modules in the headlight by a target angle. There are also approaches to automatically adjust the headlight settings in the field. For example, a driver assistance camera can record and evaluate the light distribution of the headlights in the front of the vehicle. For this type of analysis, prominent points on the cut-off line, such as an H0V0 point, are usually used. The attempt is made to identify this point in the image. In another variant, light distributions specifically designed for calibration can be emitted in suitable situations, for example during a start-up or sleep process.

[0008] Based on the distance of pixels in the camera image to a calibrated reference point, vertical and horizontal differential angles can then be estimated and compared with a currently targeted adjustment. Vertical and horizontal misalignments can thus be compensated for. However, difficulties arise from uncontrolled or uncontrollable environmental conditions. These can affect the lighting conditions as well as the structure, shape, and positioning of the illuminated surfaces. Different vehicles can also have different lighting systems. This can result in differences in color and brightness distribution, individual pixel errors, or even inaccuracies in the optical path, which can lead to blurring and color shifts.

[0009] An evaluation algorithm can be based on edge and maximum detection, in particular, but this can lead to imprecise calibration with inaccurate and variable feature extraction. In particular, safety-relevant accuracies of 0.1% according to ECE cannot be robustly maintained. The introduction of high-resolution lighting systems in vehicles, based on LCD, DMD, or pLED technologies, for example, also requires the projection of increasingly complex light distributions.

[0010] The object of the present invention is to provide a method for calibrating vehicle headlights which overcomes the aforementioned disadvantages.

[0011] According to the invention, this object is achieved by a method having the features in claim 1 and in particular in the characterizing part of claim 1. Advantageous embodiments and further developments emerge from the dependent claims.

[0012] At the core of the method according to the invention, at least three images are taken in a first step, wherein a first image is taken with an image of a calibration pattern, a second image is taken without a calibration pattern, and a third image is taken with an image of the inverse calibration pattern. In a second step, the second image is subtracted from the first and third images in order to clean up the images from an existing scene. The calibration pattern comprises circles, the position of the circles in the image is known in advance, and the centers of the circles are arranged on horizontal lines. Each circle center is calculated by means of a straight line approximation, wherein it is determined whether the projection of the calibration pattern onto a suitable surface that is suitable for performing the calibration. By subtracting the images, only the calibration pattern is visible in the image at any given time.This significantly simplifies the subsequent evaluation algorithm and allows for significantly more robust implementation. This provides a system for automatic and highly accurate calibration of the settings of high-resolution headlight systems in vehicles.

[0013] The method for calibrating vehicle headlights determines an incorrect position of a predefined light distribution by evaluating images from at least one vehicle camera. The incorrect position can then be corrected, for example, using the installed stepper motors and redefining the zero position. During calibration, the method can record the structure of the vehicle's frontal field and, in particular, indicate whether a wall is located in front of the vehicle. The orientation of the wall can also be determined. All of this information can be used to adapt projections from the headlight to the existing frontal field.

[0014] Preferably, in a third step, the first and third images can be compared pixel by pixel in order to detect a difference in brightness between pixels of the same position.

[0015] According to an advantageous embodiment, it can be provided that areas with very small differences in brightness are displayed as gray areas. For example, areas outside the calibration pattern that are also located in the camera image, i.e. in the recording, are marked as gray areas, so that they do not need to be further evaluated. This has the advantage that a background scene is displayed in a gray value that is clearly separated from the projection areas of the headlight. Furthermore, by merging the two inverse images, the influence of optical crosstalk between activated pixels due to the imperfect optical channel can be eliminated. This can, for example, improve the subsequent localization of the circles.

[0016] The calibration pattern consists of circles, the position of which in the image is known in advance. High-resolution systems allow completely different projections to be used for calibration. Therefore, circles, for example, can be used, which offer several advantages. For example, circles have a constant center point regardless of the focus of the lighting system on the projection surface. Circles are also robust against distortion.

[0017] The centers of the circles are arranged on horizontal lines. Advantageously, the positioning of the circles within the light field of the headlight is known in advance. This can be achieved, for example, by knowing the distances between parallel lines and a maximum permissible or known distance between the centers.

[0018] Using a straight line approximation, each circle center is calculated, determining whether the calibration pattern is projected onto a suitable surface for performing the calibration. For example, a required maximum rotation and the distances between the parallel lines can ensure that the projection is onto a plane. Only in this case should it be advantageous to proceed with the calibration.

[0019] According to a very advantageous development of the concept, the vehicle camera can be pre-calibrated. This is advantageous for performing the previously described straight-line approximation. A pre-calibrated vehicle camera is also advantageous for determining the position and rotation of the projection surface, i.e., the pose.

[0020] According to an advantageous embodiment, it can be provided that a pose of a projection plane is determined by rotating the calibration pattern horizontally and vertically and the pose of the projection plane is calculated by shifting the centers of the circles in the camera image. This is done in particular by assuming a flat projection surface. Therefore, in a final step, the orientation of the headlight can be determined and the associated misalignment derived via a plane pose, center point positions in the camera image, and known angular positions of the associated headlight pixels. The known angular positions can be a vertical angle to the center point and / or a horizontal angle to the center point of the circle. Likewise, or alternatively, the headlight can be calibrated in advance in order to use the circles as feature points for triangulating 3D coordinates.

[0021] Advantageously, an additional 2 x 3 images are taken for the two shifted calibration patterns. In such a case, the corresponding camera-headlight pair is used as a structured lighting system.

[0022] It is also conceivable to model projected circles as conical shells as they propagate through space. Here, too, the position of the rings in three-dimensional space can be precisely determined, and the headlight adjustment can be directly calculated, since the headlight's installation position is known, allowing the light beam to be reconstructed.

[0023] A further advantageous embodiment can provide for the pose to be determined based on known angular positions of the calibrated vehicle camera, whereby flat surfaces and discontinuous scenes can be detected in order to adapt projections and / or animations for staging to the projection plane. Advantageously, this allows for a precise measurement of the projection surface in front of the vehicle, whereby not only flat surfaces such as a wall or the roadway, but also more complex and discontinuous scenes can be detected.

[0024] Further advantages of the method according to the invention also emerge from the remaining dependent subclaims and become clear from the exemplary embodiments which are described in more detail below with reference to the figures.

[0025] Showing:

[0026] Fig. 1 shows a possible embodiment of a calibration pattern;

[0027] Fig. 2 shows another possible embodiment of a calibration pattern;

[0028] Fig. 3 shows a possible sequence of the procedure.

[0029] The illustration in Fig. 1 shows a possible embodiment of a calibration pattern 4. The calibration pattern 4 has individual circles 9, each with a center point 10. The area shows, for example, the area of ​​a headlight 13. A further embodiment of the method 1 can be seen in Fig. 2. In contrast to Fig. 1, the circles 9 are arranged differently. Furthermore, horizontal lines 11 can be seen, which run along the center points 10. With such a calibration pattern 4, vertical lines 1T can also be drawn for evaluation, which also connect two center points 10 with each other.

[0030] Fig. 3 shows a possible sequence of method 1. In the first step 2, three individual images are created. A first image 3 is taken with the calibration pattern 4. A second image 5 is taken without the calibration pattern 4. A third image 6 is taken with the inverse calibration pattern 4'. In a second step 7, the second image 5 is subtracted from the first and third images 3, 6. This allows the images 3 and 6 to be cleaned up from an individually existing scene. For reasons of clarity, the second step 7 is shown twice. In a third step 8, the two images 3, 6 are compared pixel by pixel in order to find a brightness difference between pixels in the same position. Small differences in brightness are shown as a gray area. This concerns the area outside the headlight 13, which is shown with a light dashed line.

[0031] The process thus enables simple and automatic calibration of the headlights without additional hardware components. Advantageously, a high level of accuracy can be achieved. Furthermore, the process is robust to environmental conditions and can be performed autonomously, thus requiring no intervention from a driver or other operator. This increases safety and comfort. Likewise, the profile of the projection space calculated during operation can be used to adapt the vehicle's projection, for example, startup animations for staging, to the available projection surface.

Claims

A method (1) for calibrating vehicle headlights, wherein a misalignment of a predefined light distribution is determined by evaluating images from at least one vehicle camera, characterized in that in a first step (2) at least three recordings are taken, wherein a first recording (3) includes a calibration pattern (4), a second recording (5) without a calibration pattern (4), and a third recording (6) includes the inverse calibration pattern (4'), and wherein in a second step (7) the second recording (5) is subtracted from the first and third recordings (3, 6) in order to clean the recordings (3, 6) from a present scene, wherein the calibration pattern (4) comprises circles (9), wherein the position of the circles (9) in the recording is known in advance, and wherein center points (10) of the circles (9) are arranged on horizontal lines (11), and each circle center point (10) is calculated by means of a straight line approximation,wherein it is determined whether the projection of the calibration pattern (4) is carried out onto a suitable surface suitable for performing the calibration. Method (1) according to claim 1, characterized in that in a third step (8), the first and third images (3, 6) are compared pixel by pixel in order to detect a brightness difference between pixels of the same position. Method (1) according to claim 2, characterized in that Areas with very small differences in brightness are represented as gray areas. Method (1) according to one of claims 1 to 3, characterized in that the vehicle camera is pre-calibrated. Method (1) according to one of claims 1 or 4, characterized in that a pose of a projection plane is determined by rotating the calibration pattern (4) horizontally and vertically and calculating the pose of the projection plane via a shift of the circle centers (10) in the camera image (12). Method (1) according to claims 4 and 5, characterized in that the pose is determined by known angular positions of the calibrated vehicle camera, wherein flat surfaces and discontinuous scenes can be recognized in order to adapt projections and / or animations for staging to the projection plane.

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